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Model-Driven Engineering of High-Assurance Adaptive Systems Dr. B. Cheng chengb at cse.msu

Model-Driven Engineering of High-Assurance Adaptive Systems Dr. B. Cheng chengb at cse.msu.edu. CSE891 Spring 2008. Background. Model-driven engineering Systematic refinement of models, from abstract to more concrete models Growing area of research and practice Autonomic Computing

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Model-Driven Engineering of High-Assurance Adaptive Systems Dr. B. Cheng chengb at cse.msu

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  1. Model-Driven Engineering of High-Assurance Adaptive SystemsDr. B. Chengchengb at cse.msu.edu CSE891 Spring 2008

  2. Background • Model-driven engineering • Systematic refinement of models, from abstract to more concrete models • Growing area of research and practice • Autonomic Computing • Systems that dynamically adapt in response to changing environmental conditions, user needs, and internal conditions. • Used for cyberinfrastructure protection, remote monitoring. • High Assurance Systems • Systems where execution errors may cause loss of life, injury, property damage, financial loss. • Transportation systems, military systems, financial systems.

  3. Course Objectives • Study state of the art in the cross section of these three areas MDE-AC-HAS • Create in-depth profiles of specific projects/techniques/tools • Evaluate their utility on concrete examples • Identify strengths and weaknesses; future extensions • Compile taxonomy of MDE-AC-HAS techniques with guidelines for applicability.

  4. Course Structure • Presentations/Reports of techniques • Theoretical foundations • Applicability • Comparison to related work • Discussions of strengths and weaknesses • Use and Evaluation Presentations/Empirical Report • Tutorial • In-class demonstration of technique/tool • Use of concrete examples • Class participate in example exercises • Presentation of evaluation on larger-scale example(s)

  5. Course Evaluation • Class Participation: 10% • Discussion • 1-page writeups • 1st Presentation 10% • Draft project report 10% • In-Class demonstration/evaluation 10% • Final Project report 30% • Final Evaluation report 30%

  6. First Assignment due Jan. 23 • Identify three candidate techniques to profile. • Create 6-slide presentation: • 2 slides for each technique • Problem and domain addressed • Brief summary of general technique • Validation and level of use • List of relevant papers; relevant website • Class will select 9 techniques

  7. Schedule

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